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14th MANCO

Linear Programming Approach for Irrigation Scheduling ­ A case Study

H. MD. AZAMATHULLA, Senior Lecturer, River Engineering and Urban Drainage Research Centre (REDAC), Universiti Sains Malaysia, Engineering Campus, 14300 Nibong Tebal, Pulau Pinang, Malaysia; email: [email protected], [email protected] (author for correspondence) AMINUDDIN AB GHANI, Professor, REDAC, Universiti Sains Malaysia, email: [email protected] NOR AZAZI ZAKARIA, Professor, REDAC, Universiti Sains Malaysia, email: [email protected] CHANG CHUN KIAT, Science Officer, REDAC, Universiti Sains Malaysia, email: [email protected]

Abstract There is an increasing awareness among irrigation planners and engineers to design and operate reservoir systems for maximum efficiency to maximize their benefits. Accordingly, significant work has been done on reservoir operation for known total irrigation demand and on the optimal allocation of water available to crops at the farm level.Very few studies have been conducted to derive optimal reservoir operation policies integrating the reservoir operation with the on-farm utilisation of water by the various crops. This present paper deals with the development of model -- Linear Programming (LP) -- to be applied to real-time reservoir operation in an existing Chiller reservoir system in Madhya Pradesh, India. Keywords: Cropping pattern, Water resource management, Irrigation management, Optimization



In most developing countries, a huge share of the limited budget goes to creating facilities for irrigation. Construction of reservoirs requires very high investment and also causes socioeconomic and environmental issues. Water in the reservoir has multiple claimants and needs to be optimally utilized to generate maximum benefits through proper operation, which must remain consistent despite uncertain future inflows and demands. According to the World Commission on Dams, many large storage projects worldwide are failing to produce the anticipated benefits (Labadie, 2004). Similarly, small storage projects made for local areas in developing countries, like India, are also failing to meet expectations. The main cause identified at various levels of discussion, as reported by Labadie (2004), is inadequate consideration of the more mundane operation and maintenance issues once the project is completed. For existing reservoirs, optimum operation is critical, since all the expected benefits are based on timely water releases to meet the stipulated demand. Real-time operation of a reservoir requires making relatively quick decisions regarding releases based on short-term information. Decisions are dependant on the storage in the reservoir and information available in the form of forecast hydrologic and meteorological parameters. This is especially important during floods and power generation, where the system has to respond to changes very quickly and may need to adapt rapidly (Mohan et al. 1991). For reservoir systems operated for irrigation scheduling, real-time operation is not very common because of longer decision steps. Traditionally, the reservoirs meant for irrigation purposes are operated on heuristics and certain rules derived from previous experiences. This defies the concept of water-management; much of the water is lost, which in turn leads to loss of revenue. In the early 1960s, mathematical programming techniques became popular for reservoir planning and operation; pertinent literature is available. An excellent review of the topic is given by Yeh (1985), followed by Labadie (2004) and Wurbs (1993). Along with simulation studies, Linear Programming (LP), Dynamic Programming (DP) and Non Linear Programming (NLP) are the most popular modelling techniques. A comparative study on the applicability and computational difficulties of these models is presented by Mujumdar and Narulkar (1993). Many of the aforementioned techniques have been implemented in realistic scenarios, and many reservoir systems worldwide are operated based on the decision rules generated from these techniques. However, there exists a gap between theory and practice, and full implementation has not been achieved yet (Labadie, 2004).



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